Get output feature names for transformation. Parameters ---------- input_features : array-like of str or None, default=None Input features. - If `input_features` is `None`, then `feature_names_in_` is used as feature names in. If `featu
(self, input_features=None)
| 992 | """ |
| 993 | |
| 994 | def get_feature_names_out(self, input_features=None): |
| 995 | """Get output feature names for transformation. |
| 996 | |
| 997 | Parameters |
| 998 | ---------- |
| 999 | input_features : array-like of str or None, default=None |
| 1000 | Input features. |
| 1001 | |
| 1002 | - If `input_features` is `None`, then `feature_names_in_` is |
| 1003 | used as feature names in. If `feature_names_in_` is not defined, |
| 1004 | then the following input feature names are generated: |
| 1005 | `["x0", "x1", ..., "x(n_features_in_ - 1)"]`. |
| 1006 | - If `input_features` is an array-like, then `input_features` must |
| 1007 | match `feature_names_in_` if `feature_names_in_` is defined. |
| 1008 | |
| 1009 | Returns |
| 1010 | ------- |
| 1011 | feature_names_out : ndarray of str objects |
| 1012 | Same as input features. |
| 1013 | """ |
| 1014 | # Note that passing attributes="n_features_in_" forces check_is_fitted |
| 1015 | # to check if the attribute is present. Otherwise it will pass on |
| 1016 | # stateless estimators (requires_fit=False) |
| 1017 | check_is_fitted(self, attributes="n_features_in_") |
| 1018 | return _check_feature_names_in(self, input_features) |
| 1019 | |
| 1020 | |
| 1021 | class ClassNamePrefixFeaturesOutMixin: |
nothing calls this directly
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